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scipy_analytics

SpecForgeAISpecForgeAI

Run SciPy/NumPy analytics on data provided by the user. Supports statistics, optimization, interpolation, signal processing, linear algebra, and more.

191 days ago

node_resolver

SpecForgeAISpecForgeAI

Resolve free-text business hierarchy names to node IDs using deterministic CSV lookup. Use when the user provides a desk name, team name, or hierarchy text instead of a numeric node_id. Returns node_id, confidence score, and candidate list.

191 days ago

upper_java

SpecForgeAISpecForgeAI

Uppercase input text using Java (stdin -> stdout).

191 days ago

calc_var

SpecForgeAISpecForgeAI

Calculate Value-at-Risk (VaR) for a business hierarchy node ID and as-of date by calling PyVar → UniVar. Requires a numeric node_id — if the user provides text instead, use node_resolver first to get the node_id.

191 days ago

skill_creator

SpecForgeAISpecForgeAI

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends an agent's capabilities with specialized knowledge, workflows, or tool integrations.

191 days ago

confluence_search

SpecForgeAISpecForgeAI

Search Confluence using CQL and return titles + links.

191 days ago

plot

SpecForgeAISpecForgeAI

Generate publication-quality plots using matplotlib. Supports scatter, line, bar, histogram, boxplot, heatmap, and more. Saves output as PNG to /app/output/ for download.

191 days ago

FAQ

AgentCC is a discovery hub for AI agent capabilities. We index Agent Skills as the primary dataset, and also organize MCP servers and selected AI tools so developers can quickly find, compare, and evaluate what to integrate into their workflows.
An Agent Skill is a reusable capability package for an AI agent. It can define workflows, tool usage patterns, domain knowledge, or execution rules that help the agent perform more reliably in a specific task or environment.
AgentCC is a resource and discovery layer, not a one-click installer. On each skill page, you should review the repository, file tree, install command, and usage notes, then integrate it according to the runtime or client you are using.
No. AgentCC primarily indexes external repositories and metadata. We help you understand what a skill is, where it comes from, and how it may be used, but execution and security decisions still belong to your own runtime environment.
No directory can guarantee absolute safety. AgentCC can help surface repository links, file structures, and metadata, but you should still verify permissions, external dependencies, API usage, and code quality before using a skill in production or on sensitive machines.
Yes. AgentCC is designed to be an evolving resource graph. As the submission and curation workflow matures, contributors will be able to recommend high-quality skills, MCP servers, and AI tools into the directory.
Can't find your answer here? Get in touch

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